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Applications of Machine Learning in Drug Target Discovery

[ Vol. 21 , Issue. 10 ]

Author(s):

Dongrui Gao, Qingyuan Chen, Yuanqi Zeng, Meng Jiang and Yongqing Zhang*   Pages 790 - 803 ( 14 )

Abstract:


Drug target discovery is a critical step in drug development. It is the basis of modern drug development because it determines the target molecules related to specific diseases in advance. Predicting drug targets by computational methods saves a great deal of financial and material resources compared to in vitro experiments. Therefore, several computational methods for drug target discovery have been designed. Recently, machine learning (ML) methods in biomedicine have developed rapidly. In this paper, we present an overview of drug target discovery methods based on machine learning. Considering that some machine learning methods integrate network analysis to predict drug targets, network-based methods are also introduced in this article. Finally, the challenges and future outlook of drug target discovery are discussed.

Keywords:

Drug target discovery, drug target interaction, machine learning, network-based methods, drug development, biomedicine.

Affiliation:

School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, School of Mechanical Automotive Engineering, Nanyang Institute of Technology, Nanyang 473000, School of Computer Science, Chengdu University of Information Technology, Chengdu 610225

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